A suite to build, analyze and visualize morphologies.
- NeuroM — A toolbox for analysis and processing of neuron morphologies.
- NeuroR — A collection of tools to repair morphologies.
- NeuroTS — Generation of artificial neuronal trees.
- Axon-Synthesis — Generation of artificial long-range axons in brain atlases.
- Morphology Workflows — Workflows used for morphology processing.
- NeuroMorphoVis — A toolbox to create digital reconstructions of neuronal morphologies.
- Ultraliser - Generation of high fidelity and multiscale 3D neuroscientific models.
- morph-tool — A toolbox for morphology editing.
- MorphIO — A python and C++ library for reading and writing neuronal morphologies.
- morphology-documentation — Documentation of the morphology files formats used by Blue Brain.
- BioExplorer - Extract and analyze scientific data for visualization and interactive exploration.
Useful links: GitHub repo, Documentation.
A toolbox for analysis and processing of neuron morphologies.
NeuroM is a Python toolkit for the analysis and processing of neuron morphologies.
Useful links: GitHub repo, Documentation.
A collection of tools to repair morphologies.
NeuroR is a collection of tools to repair morphologies.
Useful links: GitHub repo, Documentation.
Generation of artificial neuronal trees.
Generation of artificial neuronal trees based on the topology of biological cells and their statistical properties.
Useful links: GitHub repo, Documentation.
Long-range axon synthesis in brain atlases.
Generation of artificial long-range axon trees in brain atlases based on the Steiner-Tree algorithm for large scale structure synthesis and topological statistical properties for small scale structure synthesis.
Useful links: GitHub repo, Documentation.
Workflows used for morphology processing.
Useful links: GitHub repo, Documentation.
A toolbox to create digital reconstructions of neuronal morphologies.
A lightweight, interactive, extensible and cross-platform framework for building, visualizing and analyzing digital reconstructions of neuronal morphology skeletons extracted from microscopy stacks.
Useful links: GitHub repo, Documentation.
Reconstruction of watertight meshes, annotated volumes and center line skeletons of neuroscience spatial structures from non-watertight inputs, segmented masks, skeletons of NGV morphologies and volumes.
Ultraliser is an unconditionally robust and high-performance framework dedicated primarily to in silico neuroscience research. Ultraliser is capable of generating high fidelity and multiscale 3D models (surface meshes and annotated volumes) of neuroscientific data, such as nuclei, mitochondria, endoplasmic reticula, neurons, astrocytes, pericytes, neuronal branches with dendritic spines, minicolumns with thousands of neurons and large networks of cerebral vasculature - with realistic geometries.
Useful links: GitHub repo, Documentation.
A toolbox for morphology editing.
It aims to provide small helper programs that perform simple tasks.
Useful links: GitHub repo, Documentation.
A python and C++ library for reading and writing neuronal morphologies
MorphIO is a library for reading and writing neuron morphology files that supports swc, neurolucida asc and hdf5 as documented below.
Useful links: GitHub repo, Documentation.
This repository contains the documentation of the morphology files formats used by Blue Brain.
This is the documentation for the file formats used at Blue Brain for neurons, astrocytes and vasculatures.
The Blue Brain BioExplorer is a tool for scientists to extract and analyze scientific data for visualization and interactive exploration
Exploration relies on building software that combines data integration, analysis and interactive visualization to build, modify and navigate through large scientific datasets. For this, Blue Brain built and open-sourced the Blue Brain BioExplorer. It was originally developed to answer key scientific questions related to the Coronavirus as a use case and to deliver a visualization tool. Today, the BioExplorer allows to reconstruct, visualize, explore and describe in detail the structure and function of highly-detailed biological structures such as molecular systems, neurons, astrocytes, blood vessels, and more. You can see the first application of the BioExplorer in A Machine-Generated View of the Role of Blood Glucose Levels in the Severity of COVID-19 study.
Useful links: GitHub repo, Documentation.